Batch normalization

Batch normalization is a method for optimizing and improving of performance and stability of AI networks.

There are a lot of blog posts and online papers 📃 that explain Batch normalization. Mainly, it’s an optimization 🎚️ method for training digital models (systems) on what’s called deep learning in AI.

Huge amounts of digital data 📊 processed with basic methods of deep learning make training rather hard and demanding. The method of Batch normalization optimizes the process and makes it times more effective for deep learning in AI systems.